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AI and the Cognitive Trap
By Dr. Dennis Curry, Deputy CTO, Konica Minolta
Although not entirely realized, a form of this data simplification has already happened - since the introduction of multi-tasking operating systems (OSs), computers have been able to manage and schedule a number of activities, improving their performances enormously on the basis of user-friendly logical rules defined to optimise their resources. Today, the same kind of OSs are more present in all the connected devices that are part of our digital and cyber-worlds, becoming key entry points for the management of our businesses and lives.
So the basics are already in place. However, to keep pace with the increasing complexity of businesses and associated working practices, the concept of OSs must evolve to provide us with the sophisticated support we need. We need it to be adaptive and federated, and provide a network of cooperation and learning from and to each other.
Bearing this in mind, a natural next step could be a type of operating system based on AI, which can orchestrate several OSs and manage complexity to help people and organizations derive greater benefit from their data and environment. Unfortunately, it’s not as easy said as done, and there are several challenges to be overcome to achieve this new type of cognitive OS.
One of the challenges is that the current solutions focus only on AI algorithms and platforms for specific applications in the short term while missing the bigger picture in the longer term. To thrive, AI-based OSs will need to act as cognitive AI integrators, and augment what will be a growing commoditization of algorithms.
The focus of any AI concept in today’s age should be improving the way in which we work, connecting with other individuals and supporting better decision making
We also need to consider that the majority of AI systems are typically divided into two categories:
1. The ‘one-to-one’ type focusing on individuals including personal assistants that, for example, use Natural Language Understanding (NLU) to provide basic solutions and services for the consumer mass-market; or
2. The customised high-scale AI platforms that have been developed for entire businesses and are mainly aimed at working on large data-sets for large-scale needs.
Both of these types of systems were built predominantly to satisfy the requirements of cost, security, and stability, which is satisfactory enough. However, their ruling logic has had to suit everybody, and in being so open, the possibility of customisation to then meet the needs of individuals is limited. It’s a cognitive trap.
To exploit the true potential of AI, we need to move away from this trap, and the solution lies in the form of distributed OS applications that occupy a new middle ground. These systems can integrate and orchestrate AI services to enable better team working and collaboration among individuals; allowing small, medium and large enterprises to access distributed intelligent information and edge devices seamlessly, interfacing with smartphones and tablets, and supporting enterprises in taking decisions that are more objectively based.
When we then apply this to really transform the role of technology in the workplace, systems need to be designed to learn and predict the needs of the user, rather than be based on self-defined logic from individual applications. As we switch between operational, tactical, and strategic tasks, users should be able to create, organize and browse information through a single-entry point. The focus of any AI concept in today’s age should be improving the way in which we work, connecting with other individuals and supporting better decision making.
Within the context of a working environment, where collaboration is often a critical element for successful execution, AIs will need to learn about how people gather information, how they analyze its context, how they then take decisions and finally about how they perform actions – all within a seamless process. Moreover, the fundamentals of human communication including facial expression, gestures, and speech, should be integrated into a truly multi-modal interface, to offer that flexibility so many looks for in today’s expanding dimensional world.
In the end, it all links back to the same point – AI has the greatest potential in tomorrow’s world, and if executed properly will become the center of augmenting our intelligence and the wider workplace transformation. As an emerging type of operating system, it will help orchestrate the physical and digital resources of the workplace of the future, to enable organizations to make more insightful business decisions. At Konica Minolta, we’re exploring ways to develop this further, with an AI-based operating system known as Cognitive Hub.
See Also: Top Artificial Intelligence Companies